Ma Group

Light and shadow in sightseeing

Tourist boom

Thanks to the strategic relaxation of the visa policy, tax exemption and the bold reforms of the Abe cabinet, the number of tourists and their economies are expanding day by day. The tourism agency has set goals for 10 years and 20 years from now, and aims to increase the number of tourists, travel consumption and foreigners by several times. However, how to achieve that is the question being asked.

Bias of tourist places

According to the Tourism Agency, accommodation for foreign tourists visiting Japan is concentrated in cities such as Tokyo, Osaka, and Kyoto. The concentration of the location and time of sightseeing in the urban area limits the benefits to the entire regions. In addition, if the number of tourist cities is limited, there is a concern that the repeater's return rate will also be low due to the narrowing of tourism resources.

Limits of advertising

In the tourist areas for a provincial city, it is very difficult to raise the name recognition. Although Kamakura and Nara are very famous domestically in Japan, most foreign tourists do not know them. In terms of cost effectiveness, it is also difficult to promote these provincial cities to foreigners visiting Japan.

Tourism 2.0

In order to deal with various problems in tourism, it is necessary to evolve from service provider-centered tourism 1.0 to user-led tourism 2.0. Tourism 2.0 collects and analyzes regional and user opinions at low cost, on a large scale, and in a timely manner, using UGC (User Generated Contents) by transmitting information on their own. UGC, which is generated based on the user's tourism experience, is an important source of travel planning, tourism resource rediscovery and promotion. Also, analysis and utilization of “tourism knowledge” from the user's point of view, such as, research on tourism knowledge mining has been actively conducted.

Spreading tourism pollution

While tourists have increased, dissatisfaction from residents against tourists has also increased. Although it becomes convinient to travel by renting private residences, the manners of tourists are being asked at the same time. In addition, it is also a problem that traffic congestion and noise on the road caused by crowded tourists will inspire dislike in local residents.

Papers

  • 1. Yang Zhang and Qiang Ma: Dual Attention Model for Citation Recommendation, COLING 2020 (The 28th International Conference on Computational Linguistics):3179-3189, 2020.12.
  • 2. Satoshi Yoshida, Qiang Ma: Generating Dialogue Sentences to Promote Critical Thinking, DEXA (1) 2020: 354-368, 2020.9
  • 3. Junjie Sun, Tomoki Kinoue, Qiang Ma: A City Adaptive Clustering Framework for Discovering POIs with Different Granularities, DEXA (1) 2020: 425-434, 2020.9
  • 4. 7. T. Chen and Q. Ma: Discriminative Object Discovery Toward Personalized Sightseeing Spot Recommendation, BIGMM2019:208-212, doi: 10.1109/BigMM.2019.00-24, 2019.9
  • 5. Junjie SUN, Chenyi ZHUANG, and Qiang MA: User Transition Pattern Analysis for Travel Route Recommendation, IEICE Transactions 102-D(12):2472-2484 (2019)
  • 6. Kenki Nakamura, Qiang Ma: Context-Aware GANs for Image Generation from Multimodal Queries, DEXA2019:429-443.
  • 7. Sheng Hu, Chuan Xiao, Jianbin Qin, Yoshiharu Ishikawa, and Qiang Ma: Autocompletion for Prefix-Abbreviated Input, SIGMOD 2019:211-228.
  • 8. Junjie Sun, Chenyi Zhuang, and Qiang Ma. "Travel Route Recommendation by Considering User Transition Patterns." e-Review of Tourism Research 16.2/3, 2019
  • 9. 馬強，“観光の分散化と個人化の実現に向けたユーザ生成コンテンツの分析と利活用技術について”，システム／制御／情報　63巻1号:33-38, 2019
  • 10. Min Ge, Chenyi Zhuang, Qiang Ma, “Robust visual object clustering and its application to sightseeing spot assessment”, Multimedia Tools and Applications ():1-30, http://dx.doi.org/10.1007/s11042-018-7066-2, 2019
  • 11. Chenyi Zhuang, Qiang Ma:Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification. WWW 2018: 499-508
  • 12. Yizhu Shen, Min Ge, Chenyi Zhuang, Qiang Ma: Sightseeing value estimation by analysing geosocial images. IJBDI 5(1/2): 31-48 (2018)
  • 13. Chenyi Zhuang, Qiang Ma, and Masatoshi Yoshikawa： SNS user classification and its application to obscure POI discovery, Multimedia Tools and Applications　76(4): 5461-5487，2017
  • 14. 馬強：観光情報学の最前線ー観光の分散化と個人化を促進する集合知活用情報技術ー，情報処理学会誌　58(3): 220 - 226，2017
  • • 総務省 SCOPE（社会展開指向型研究開発），「観光の個人化と分散化を促進する情報推薦基盤と地域観光支援システムの構築」，2020－
  • • 科学研究費補助金（挑戦的萌芽），「UGCを用いた人気度と観光価値の自動評価に基づく穴場観光スポットの発見」，2016－2019